I've seen 100 people make this statement and mean 100 different things, so I just wanted to clarify:
How are you defining "reasoning" here as distinct from statistical correlation?
That's a superficial definition in the sense that it doesn't account for how that line of thought is generated: in humans, this is often a combination of statistical correlation and transfer learning (e.g. I have observed round things hitting perpendicular surfaces and assume that that transfers here).
1. http://en.wikipedia.org/wiki/Correlation_does_not_imply_caus...
A couple points here:
* The way humans model causation is just non-naive statistical correlation (controlling for variables). That technique is still accurately described as "statistical correlation"
* I'm not even convinced that human reasoning _does_ imply generating a model of causation. Let's exclude things like rigorous scientific studies for the purpose of the discussion and focus on day-to-day human reasoning: I think the thought processes of most of the people I know could most accurately be explained by correlating things across time. Modeling causation is often incidental (X often happens after Y is a reasonable enough heuristic for general use).
I think you'll need to look at the other end of the spectrum to see an abundance of (wrong?) models of causality: Religion and Law.
There are no "confirmed" cases of anyone actually going to heaven or hell or purgatory (or whatever else), and yet many of us still conform to some arbitary ruleset in the hopes of eventually ending (or not ending) up in one of thoses places, because we have constructed some model of how doing this gets you into hell and doing that gets you into heaven.
Similarly, we have plenty of evidence on how companies spend huge effort on finding loopholes in tax laws in order to avoid taxes, and yet instead of simplyfing the ruleset (so that there are obviously no holes in it) we still opt for piling on more laws (so that there are no obvious holes in it) because we construct (faulty?) models of how those new rules will prevent further exploits.
Sure, the rule of inference may have ultimately been derived from experience, by a process which in some sense involved statistical correlation. But you have to distinguish that ultimate basis for the inference rule from _the process of logical inference itself_. It's the latter that is generally called reasoning.
Reasoning in the above sense is essential to intelligence, even at the toddler level, and the DeepMind work doesn't address reasoning. I think that may be the point the parent was getting at.
[1] To be clear, I'm not dismissing a viewpoint that I think is wrong as "unmoored from logic", I'm specifically talking about the very common situation where people confidently assert this with no attempt (and no ability) to back it up in any way other than confidence that intelligence is simply natural and non-biological entities can never get arbitrarily close.
We don't naturally reason through potential causes like "Mass exerts a gravitational force which attracts other mass."
That's my layman opinion, that seems to agree with the etymology of reason. Reason > ... > Ratio ... Reor. Reor is latin for to think, or calculate. Arithmetic in its simplest form, addition in the unary system ie. arranging pebbles (= lt. calculus), counting knots, simply counting. Now backtracking is just enumeration and elimination of possibilities. Ratio itself means measure, and a measurement always entails statistical error (does heisenbergs uncertainty principle prove that?).
It could probably solve a maze quite easily if the entire maze fit on screen. That problem requires no memory. If it had to make decisions based on information not present on screen, it would fail.